Principal Data Scientist, Oncology

Johnson & Johnson

Quick summary

Work type
On-site
Location
Spring House, PACambridge, MASan Diego, CARaritan, NJTitusville, NJ
Salary
$117,000–$201,250 / yr
Posted
2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $167k
This role $159k
$104k most similar roles pay here $238k

This role pays less than 66% of similar roles. Most pay $133,750–$200,596 — the shaded band above. At the midpoint, this role pays about $159k versus about $167k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 68 open roles on FindRole.

Listed pay typically runs $117,000–$201,250 across 65 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist, Oncology

The Principal Data Scientist - Oncology role at Johnson & Johnson Innovative Medicine involves joining the Data Science and Digital Health team to standardize and connect biomedical and clinical data for oncology research and development. This hands-on position requires designing and implementing a scalable knowledge graph infrastructure, applying graph-based data modeling, and working with SPARQL/GraphQL/REST services to develop ingestion pipelines. The candidate will also extend ontologies using RDF standards, curate datasets, and collaborate with cross-functional teams to enable natural language processing over graphs for predictive modeling. Essential skills include experience in semantic technologies, large-scale knowledge graphs, and proficiency in graph databases like Neo4j and Amazon Neptune, along with a background in bioinformatics or related fields. The role demands expertise in CI/CD implementations, DevOps tools, and the ability to manage multiple projects while ensuring high availability and scalability of the database infrastructure.

What you'll do

  • Design and implement a scalable knowledge graph infrastructure for Oncology R&D data.
  • Apply graph-based data modeling to organize, integrate, and retrieve Oncology R&D data efficiently.
  • Standardize and curate datasets with Data Scientists and Clinical Scientists for AI readiness.
  • Extend ontologies using RDF standards to map into established biomedical ontologies accurately.
  • Develop ingestion pipelines to normalize and map concepts across various data sources.
  • Draft documentation such as data dictionaries and lineage diagrams to facilitate knowledge graph understanding.

What we're looking for

  • PhD or Master's degree in bioinformatics, computer science, or related fields with focus on semantic technologies for biomedical applications.
  • 5+ years of professional experience in health informatics and large-scale knowledge graph construction.
  • Expertise in programming with parser combinators, natural language processing, and linked data (RDF Triple Stores).
  • Proficiency in semantic web technologies including SPARQL, RDF, OWL, and familiarity with Neo4j or Amazon Neptune.
  • Experience working with complex biomedical datasets such as clinical, genomics, and proteomics data.
  • Strong background in various data storage solutions and data modeling techniques for semantic data and ontologies.

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